Triple
T15812536
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flemish Ardennes |
E383389
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Ronse |
E570884
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Ronse | Statement: [Flemish Ardennes, contains, Ronse]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ronse Context triple: [Flemish Ardennes, contains, Ronse]
-
A.
Ronse
chosen
Ronse is a small city in western Belgium known for its textile-industry heritage and location in the hilly Flemish Ardennes.
-
B.
Morangis
Morangis is a commune in the southern suburbs of Paris, located in the Essonne department in the Île-de-France region of northern France.
-
C.
Beaufays
Beaufays is a village in the municipality of Chaudfontaine in the province of Liège, Belgium.
-
D.
Borgentreich
Borgentreich is a small town in North Rhine-Westphalia, Germany, known for its rural character and historic churches.
-
E.
Lerse
Lerse is a supporting character in Johann Wolfgang von Goethe’s play "Götz von Berlichingen," known as a loyal and brave follower of the titular knight.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d86da2858c819090cc8481e7207b6e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0c4a069bc8190bf9504dc6c998fa2 |
completed | April 16, 2026, 11:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff9993c86c8190b1d106af7537080a |
completed | May 9, 2026, 8:31 p.m. |
Created at: April 10, 2026, 4:49 a.m.